efangs

exactly, thank you

how is this new? evolutionary heuristics have been around for a long time. why give it a new name?

sorry this is not fast

This is dumb because it's literally doing what it has been instructed to do, as well as given access to means to carry out those actions. Just another hype mechanism for OpenAI.

From my experience, pihole is very easy to setup for this use case: https://pi-hole.net/

everyone should just have a pihole

OK explain to me why I have to book a campsite 6 months in advance

I feel like this is missing a "know when it's time to call it quits" section.

fun tool, but tbh I found it frustrating right out of the gate. It felt like being stuck in an infinite loop. https://practiceinterview.co/interview/330?key=36a0893b-6a2b...

You might want to check your timezone settings.

Yes

I was with the article until this final point about integrated solutions. I see the argument around data lock-in, but integration is typically non-trivial unless it's coming from the same provider. Plus, I'm certain cloudflare would equally love to provide more services in an integrated way.

In your demo, I got to the point of "Click Metrics to continue...", and "Metrics" was unclickable: https://imgur.com/a/i5LWFaa

I'm using FireFox 86.0 on MacOS 11.2 (Apple M1 chip).

Is it possible to backfill a materialized view? I'm maybe confused, but does this potentially replace a traditional data lake or is it specifically for streaming applications?

We the OpenAI board have decided it would benefit all humanity for us to claim 100x profits.

This will be nice until they take it away...

Is it? How many hours for you to set up something similar, and then what do you get paid per hour?

Ah ok, yeah TBH I didn't read the article, but was guessing from the headline this is what they meant since in exponentially scaling problems theres always room at the top (unless explicitly proven otherwise).

Title could also be "Researchers find a better heuristic for a class of exponentially scaling problems."

There's no claim to have changed the complexity class, so"exponentially faster" just means the problem is still exponentially in problem size, but the exponent is smaller.

From the looks of it, though, it is a nice result because it has pretty wide applicability.

This plot essentially ignores all other computational science. People in HPC have been operating at these scales for awhile, and yet don't make claims about their field taking over the world.

It's true that at 50-100 physical (not logical) qubits, it's no longer possible to simulate classically. That does not mean that they are useful.

As other people pointed out, you may need a factor of 100-1000 more physical qubits to get as many logical qubits.

YES. Exactly this.

It's fine to make approximations to avoid exponential scaling, but applying function approximators essentially randomly won't get you anywhere. This is then compounded by the fact that the functional framework you're starting from is not a first-principles approach.

Until there is QMC for drug discovery, it will all be hype.

"making it many times easier to add support for GPUs"

Can it use Chromecast?

Cool! I made (almost the exact same) thing as a twitter bot awhile ago: https://twitter.com/sub500

or "THEM"

Anyone use collectd + rrd for this purpose? Still trying to understand at what level it's worth to move to something else.

A single Dwave is not faster than a cluster of CPUs.

Is a cluster of Dwaves faster than a cluster of CPUs? Maybe at the two problems Google looked at.

If you give classical k cores, then to be fair you should give quantum k D-waves. If you are only making a scaling argument, then no need to include terms that cancel.

If you want to make a comparison between currently available hardware, then the metric should be some combination of speed, power usage, space, cost, etc.

Because both D-wave and the classical algorithms will benefit linearly with parallelization.

If they want to make a claim about the scaling ratio between D-wave and classical algorithms, then this linear term would cancel.